Balancing supply and demand in the presence of renewable generation via demand response for electric water heaters
提出多阶段随机优化模型，计算电热水器群体平均热能的最优日前目标曲线，以平抑风电和不可控负荷波动带来的净需求变化。
With the increasing presence of renewable energy sources in the electrical power grid, demand response via thermostatic appliances such as electric water heaters is a promising way to compensate for the significant variability in renewable power generation. We propose a multistage stochastic optimization model that computes the optimal day-ahead target profile of the mean thermal energy contained in a large population of heaters, given various possible wind power production and uncontrollable load scenarios. This optimal profile is calculated to make the variable net demand as even as possible.